R Figure 2
suppressPackageStartupMessages({
library(Seurat)
library(Signac)
library(BSgenome.Drerio.UCSC.danRer11)
library(EnhancedVolcano)
library(ggsci)
library(patchwork)
})Read data
HB13 <- readRDS(file = "../data/HB13hpf_neural.RDS")
DefaultAssay(HB13) <- "SCT"
Idents(HB13) <- "Clusters"HB16 <- readRDS(file = "../data/HB16hpf_neural.RDS")
DefaultAssay(HB16) <- "SCT"
Idents(HB16) <- "Clusters"HB.int <- readRDS(file = "../data/int.neural.3WT.subset.RDS")
DefaultAssay(HB.int) <- "SCT"
Idents(HB.int) <- "intClusters"Cluster names
HB13hpf
Named clusters after clustering at resolution 8, needed to resolve all rhombomeres into separate clusters.
DimPlot(HB13, reduction = "wnn.umap") + scale_color_igv()
Combining multiple clusters of same cell type.
Idents(HB13) <- "Clusters"
HB13 <- RenameIdents(HB13,
"r5.1" = "r5",
"r5.2" = "r5",
"MB.1" = "MB",
"MB.2" = "MB",
"MB.3" = "MB",
"MHB.1" = "MHB",
"MHB.2" = "MHB",
"MHB.3" = "MHB",
"MHB.4" = "MHB",
"MHB.5" = "MHB",
"FB.1" = "FB",
"FB.2" = "FB",
"FB.3" = "FB",
"FB.4" = "FB")## Warning: Cannot find identity r5.2## Warning: Cannot find identity r5.1levels(HB13) <- c("FB","MB","MHB","r1","r1 & r2","r2","r3","r4","r5","r6",
"low_expression","unknown","Neuron","Ciliated","CHB.1","CHB.2","CHB.3","SC.1","SC.2","SC.3")
umap.HB13 <- DimPlot(HB13, reduction = "wnn.umap") + scale_color_igv() +
guides(color = guide_legend(override.aes = list(size=4), ncol=2) )
umap.HB13
HB16hpf
Named clusters after clustering at resolution 6, needed to resolve all rhombomeres into separate clusters.
DimPlot(HB16, reduction = "wnn.umap") + scale_color_igv()
Combining multiple clusters of same cell type.
Idents(HB16) <- "Clusters"
HB16 <- RenameIdents(HB16,
"r5.1" = "r5",
"r5.2" = "r5",
"MB.1" = "MB",
"MB.2" = "MB",
"MHB.1" = "MHB",
"MHB.2" = "MHB",
"MHB.3" = "MHB")
levels(HB16) <- c("FB","MB","MHB","r1","r2","r3","r4","r5","r6",
"DorsNT & NC","Neuron","Ciliated","CHB.1","CHB.2","CHB.3","CHB.4","SC.1","SC.2","SC.3")
umap.HB16 <- DimPlot(HB16, reduction = "wnn.umap") + scale_color_igv() +
guides(color = guide_legend(override.aes = list(size=4), ncol=2) )
umap.HB16
## HB integrated
Idents(HB.int) <- "intClusters"
HB.int <- RenameIdents(HB.int,
"r1&r2.1" = "r1 & r2",
"r1&r2.2" = "r1 & r2",
"r3.1" = "r3",
"r4.1" = "r4",
"r4.2" = "r4",
"r5.1" = "r5",
"r5.2" = "r5",
"r6.1" = "r6",
"r6.2" = "r6",
"MB.1" = "MB",
"MB.2" = "MB",
"MB.3" = "MB",
"MHB.1" = "MHB",
"MHB.2" = "MHB",
"MHB.3" = "MHB",
"MHB.4" = "MHB",
"MHB.5" = "MHB",
"MHB.6" = "MHB",
"Neuron.1" = "Neuron",
"Neuron.2" = "Neuron",
"CaudHB.1" = "CHB.1",
"CaudHB.2" = "CHB.2",
"CaudHB.3" = "CHB.3",
"CaudHB.4" = "CHB.4")
levels(HB.int) <- c("MB","MHB","r1 & r2","r1","r2","r3","r4","r5","r6",
"CHB.1","CHB.2","CHB.3","CHB.4","SC.1","SC.2","SC.3","SC.4",
"Neuron","Ciliated","Neurog","NC.1","NC.2","HB","Mitochondrial")
umap.HBint <- DimPlot(HB.int, reduction = "wnn.umap") + scale_color_igv() +
guides(color = guide_legend(override.aes = list(size=4), ncol=2) )
umap.HBint
Gene expression and chromvar activity plots
HB13hpf
HB13.casz1 <- FeaturePlot(HB13, features = "casz1", reduction = "wnn.umap", max.cutoff = 1.3) + NoLegend()
HB13.zic2b <- FeaturePlot(HB13, features = "zic2b", reduction = "wnn.umap", max.cutoff = 1.3)
HB13.ntn1a <- FeaturePlot(HB13, features = "ntn1a", reduction = "wnn.umap", max.cutoff = 1.3) + NoLegend()
HB13.sp8a <- FeaturePlot(HB13, features = "sp8a", reduction = "wnn.umap", max.cutoff = 1.3) + NoLegend()
HB13.lbx1b <- FeaturePlot(HB13, features = "lbx1b", reduction = "wnn.umap", max.cutoff = 1.3) + NoLegend()HB13.plots <- umap.HB13 + HB13.casz1 + HB13.zic2b + HB13.ntn1a + HB13.sp8a + HB13.lbx1b +
plot_layout(ncol = 3)
HB13.plots
HB16hpf
HB16.zic2b <- FeaturePlot(HB16, features = "zic2b", reduction = "wnn.umap", max.cutoff = 1.3) + NoLegend()
HB16.ntn1a <- FeaturePlot(HB16, features = "ntn1a", reduction = "wnn.umap", max.cutoff = 1.3)
HB16.lbx1b <- FeaturePlot(HB16, features = "lbx1b", reduction = "wnn.umap", max.cutoff = 1.3) + NoLegend()
HB16.dbx1b <- FeaturePlot(HB16, features = "dbx1b", reduction = "wnn.umap", max.cutoff = 1.3) + NoLegend()HB16.plots <- umap.HB16 + HB16.zic2b + HB16.ntn1a + HB16.lbx1b + HB16.dbx1b +
plot_layout(ncol = 3)
HB16.plots
HB integrated
HBint.zic2b <- FeaturePlot(HB.int, features = "zic2b", reduction = "wnn.umap", max.cutoff = 1.3) + NoLegend()
HBint.lbx1b <- FeaturePlot(HB.int, features = "lbx1b", reduction = "wnn.umap", max.cutoff = 1.3)
HBint.dbx1b <- FeaturePlot(HB.int, features = "dbx1b", reduction = "wnn.umap", max.cutoff = 1.3) + NoLegend()
HBint.ntn1a <- FeaturePlot(HB.int, features = "ntn1a", reduction = "wnn.umap", max.cutoff = 1.3) + NoLegend()HBint.plots <- umap.HBint + HBint.zic2b + HBint.lbx1b + HBint.dbx1b + HBint.ntn1a +
plot_layout(ncol = 3)
HB16.plots
Figure 2 combined plots
layout <- "
ABC
DEF
GHI
#JK
LMN
#OP"
combined <- umap.HB13 + HB13.casz1 + HB13.zic2b +
HB13.ntn1a + HB13.sp8a + HB13.lbx1b +
umap.HB16 + HB16.zic2b + HB16.ntn1a +
HB16.lbx1b + HB16.dbx1b +
umap.HBint + HBint.zic2b + HBint.lbx1b +
HBint.dbx1b + HBint.ntn1a +
plot_layout(design = layout)
combined
ggsave(filename = "Plots/Figure2.png", width = 15, height = 20, plot = combined)umap.HB13 <- umap.HB13 +
guides(color = guide_legend(override.aes = list(size=4), ncol=1) )
umap.HB16 <- umap.HB16 +
guides(color = guide_legend(override.aes = list(size=4), ncol=1) )
umap.HBint <- umap.HBint +
guides(color = guide_legend(override.aes = list(size=4), ncol=1) )
layout <- "
AABC#
AADEF
GGHI#
GGJK#
LLMN#
LLOP#"
combined2 <- umap.HB13 + HB13.casz1 + HB13.zic2b +
HB13.ntn1a + HB13.sp8a + HB13.lbx1b +
umap.HB16 + HB16.zic2b + HB16.ntn1a +
HB16.lbx1b + HB16.dbx1b +
umap.HBint + HBint.zic2b + HBint.lbx1b +
HBint.dbx1b + HBint.ntn1a +
plot_layout(design = layout)
combined2
ggsave(filename = "Plots/Figure2_vs2.png", width = 15, height = 20, plot = combined2)sessionInfo()## R version 4.2.3 (2023-03-15)
## Platform: aarch64-apple-darwin20 (64-bit)
## Running under: macOS Monterey 12.6.2
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] patchwork_1.1.2 ggsci_3.0.0
## [3] EnhancedVolcano_1.16.0 ggrepel_0.9.3
## [5] ggplot2_3.4.2 BSgenome.Drerio.UCSC.danRer11_1.4.2
## [7] BSgenome_1.66.3 rtracklayer_1.58.0
## [9] Biostrings_2.66.0 XVector_0.38.0
## [11] GenomicRanges_1.50.2 GenomeInfoDb_1.34.9
## [13] IRanges_2.32.0 S4Vectors_0.36.2
## [15] BiocGenerics_0.44.0 Signac_1.10.0
## [17] SeuratObject_4.1.3 Seurat_4.3.0.1
##
## loaded via a namespace (and not attached):
## [1] fastmatch_1.1-3 systemfonts_1.0.4
## [3] plyr_1.8.8 igraph_1.4.2
## [5] lazyeval_0.2.2 sp_1.6-0
## [7] splines_4.2.3 BiocParallel_1.32.6
## [9] listenv_0.9.0 scattermore_1.0
## [11] digest_0.6.31 htmltools_0.5.5
## [13] fansi_1.0.4 magrittr_2.0.3
## [15] tensor_1.5 cluster_2.1.4
## [17] ROCR_1.0-11 globals_0.16.2
## [19] matrixStats_0.63.0 spatstat.sparse_3.0-1
## [21] colorspace_2.1-0 textshaping_0.3.6
## [23] xfun_0.39 dplyr_1.1.2
## [25] crayon_1.5.2 RCurl_1.98-1.12
## [27] jsonlite_1.8.4 progressr_0.13.0
## [29] spatstat.data_3.0-1 survival_3.5-5
## [31] zoo_1.8-12 glue_1.6.2
## [33] polyclip_1.10-4 gtable_0.3.3
## [35] zlibbioc_1.44.0 leiden_0.4.3
## [37] DelayedArray_0.24.0 future.apply_1.10.0
## [39] abind_1.4-5 scales_1.2.1
## [41] spatstat.random_3.1-4 miniUI_0.1.1.1
## [43] Rcpp_1.0.10 viridisLite_0.4.2
## [45] xtable_1.8-4 reticulate_1.28
## [47] htmlwidgets_1.6.2 httr_1.4.6
## [49] RColorBrewer_1.1-3 ellipsis_0.3.2
## [51] ica_1.0-3 farver_2.1.1
## [53] pkgconfig_2.0.3 XML_3.99-0.14
## [55] sass_0.4.6 uwot_0.1.14
## [57] deldir_1.0-6 utf8_1.2.3
## [59] labeling_0.4.2 tidyselect_1.2.0
## [61] rlang_1.1.1 reshape2_1.4.4
## [63] later_1.3.1 munsell_0.5.0
## [65] tools_4.2.3 cachem_1.0.8
## [67] cli_3.6.1 generics_0.1.3
## [69] ggridges_0.5.4 evaluate_0.21
## [71] stringr_1.5.0 fastmap_1.1.1
## [73] ragg_1.2.5 yaml_2.3.7
## [75] goftest_1.2-3 knitr_1.42
## [77] fitdistrplus_1.1-11 purrr_1.0.1
## [79] RANN_2.6.1 pbapply_1.7-0
## [81] future_1.32.0 nlme_3.1-162
## [83] mime_0.12 RcppRoll_0.3.0
## [85] compiler_4.2.3 rstudioapi_0.14
## [87] plotly_4.10.1 png_0.1-8
## [89] spatstat.utils_3.0-2 tibble_3.2.1
## [91] bslib_0.4.2 stringi_1.7.12
## [93] highr_0.10 lattice_0.21-8
## [95] Matrix_1.6-1.1 vctrs_0.6.2
## [97] pillar_1.9.0 lifecycle_1.0.3
## [99] spatstat.geom_3.1-0 lmtest_0.9-40
## [101] jquerylib_0.1.4 RcppAnnoy_0.0.20
## [103] data.table_1.14.8 cowplot_1.1.1
## [105] bitops_1.0-7 irlba_2.3.5.1
## [107] httpuv_1.6.9 R6_2.5.1
## [109] BiocIO_1.8.0 promises_1.2.0.1
## [111] KernSmooth_2.23-21 gridExtra_2.3
## [113] parallelly_1.35.0 codetools_0.2-19
## [115] MASS_7.3-60 SummarizedExperiment_1.28.0
## [117] rjson_0.2.21 withr_2.5.0
## [119] GenomicAlignments_1.34.1 sctransform_0.3.5
## [121] Rsamtools_2.14.0 GenomeInfoDbData_1.2.9
## [123] parallel_4.2.3 grid_4.2.3
## [125] tidyr_1.3.0 rmarkdown_2.21
## [127] MatrixGenerics_1.10.0 Rtsne_0.16
## [129] spatstat.explore_3.1-0 Biobase_2.58.0
## [131] shiny_1.7.4 restfulr_0.0.15